Improving Constraint Satisfaction Algorithm Efficiency for the AllDifferent Constraint
December 07, 2020 Β· Declared Dead Β· π arXiv.org
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Authors
Geoff Harris
arXiv ID
2012.03624
Category
cs.AI: Artificial Intelligence
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Combinatorial problems stated as Constraint Satisfaction Problems (CSP) are examined. It is shown by example that any algorithm designed for the original CSP, and involving the AllDifferent constraint, has at least the same level of efficacy when simultaneously applied to both the original and its complementary problem. The 1-to-1 mapping employed to transform a CSP to its complementary problem, which is also a CSP, is introduced. This "Dual CSP" method and its application are outlined. The analysis of several random problem instances demonstrate the benefits of this method for variable domain reduction compared to the standard approach to CSP. Extensions to additional constraints other than AllDifferent, as well as the use of hybrid algorithms, are proposed as candidates for this Dual CSP method.
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